What is the difference between a stacked restricted Boltzmann machine and deep belief network?
For what it's worth, Wikipedia says that 


  deep belief networks can be formed by "stacking" RBMs. 


Hinton writes in Scholarpedia: 


  A deep belief net can be viewed as a composition of simple learning modules each of which is a restricted type of Boltzmann machine.


So, a deep belief network is definitely a stacked RBM. 

I have never heard of different stacked RBMs, but it is easy to imagine something like convolutional stacked RBMs, where some RBMs are used as filters that slide over the input data or something. Whether that would still be called a deep belief network, is probably up to the guy who publishes it first.